Singer Identification

Singer identification research focuses on automatically recognizing singers from audio recordings, addressing challenges posed by variations in singing style, recording quality, and the increasing prevalence of cloned voices. Current efforts leverage deep learning models, particularly convolutional and recurrent neural networks, often incorporating contrastive learning and self-supervised techniques to learn robust singer embeddings from diverse datasets. This field is crucial for copyright protection, music information retrieval, and applications in virtual environments like the metaverse, where accurate singer identification is essential for authenticity and user experience.